Embodiments of the present application relate generally to systems and methods for radiological imaging. Particularly, certain embodiments relate to techniques for grouping radiological image data based on selected images in a study.
In radiology workflow, a clinician (e.g., radiologist) may read a study by traversing the images in the study. During this reading, some of the image(s) in the study may be of special interest to the clinician, and may be marked as significant, or key image(s). If a study contains a relatively large number of images, traversing the images to find key images may require multiple traversals.
The study may involve imaging of a patient's body part over a period of time, for example. Therefore, the images in the study may have a range of temporal positions. Within such time-based studies, certain events may be particularly clinically relevant. Some such clinically relevant events may include cardiac studies with more than one scan of the heart. Clinically relevant images can be found in one scan, and it may be helpful to link these images with other scans to facilitate diagnosis.
In some instances where there are multiple key images, which are spatially distributed in a study. During a radiology reading, a clinician may be interested in images that neighbor a key image. If the study contains multiple key images and the clinician wants to analyze the neighboring images, the clinician may wish to traverse the entire study and/or may wish to mark all the images neighboring to the key images as key images, for example. Reading workstations, such as PACS workstations, may not facilitate the capability for grouping neighboring images of key images into key image sequences, or events, for further reading.
The clinician may wish to read a study more than once. In such cases, it may be useful to mark an event for future reference. Present radiological workflow may not facilitate the clinician to group neighboring images of key images for future reading. It may be helpful, for example, to allow a user to mark events, which are significant, where these event markers may be accessed quickly for future reference. Furthermore, it may be useful to provide event markers that facilitate traversal of key images.
In an integrated volume rendering application, it may further be useful to provide event marker(s) which may be used to identify images, which belong to a volume segment. Such marker(s) may be employed to mark events in a volumetric radiological study.
In addition to marking events, a clinician may prefer to have certain image processing techniques to enhance clinical diagnosis of images in event marker(s). It also may be that clinical diagnosis of images in event markers(s) may be facilitated by a variety of image processing techniques. Thus, from one event marker to the next, it may be helpful to a clinician to apply different image processing algorithms.
Thus, there is a need for methods and systems that provide for the selection of images as event markers in a study. There is a need for methods and systems that improve the efficiency of study navigation for clinicians focusing on images which are key to the diagnostics. There is a need for methods and systems that provide event marking for volume rendering applications. Additionally, there is a need for methods and systems that provide image processing corresponding to images specified in event markers.